Hyperspectral anomaly detection via density peak clustering
In the last few years, a density peak clustering algorithm (DP) has demonstrated its
advantages in hyperspectral data analysis and processing. In this letter, we take the benefits …
advantages in hyperspectral data analysis and processing. In this letter, we take the benefits …
Hyperspectral anomaly detection using dual window density
Hyperspectral anomaly detection is one of the most active topics in hyperspectral image
(HSI) analysis. The fine spectral information of HSIs allows us to uncover anomalies with …
(HSI) analysis. The fine spectral information of HSIs allows us to uncover anomalies with …
Unsupervised anomaly and change detection with multivariate gaussianization
JA Padrón-Hidalgo, V Laparra… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Anomaly detection (AD) is a field of intense research in remote sensing (RS) image
processing. Identifying low probability events in RS images is a challenging problem given …
processing. Identifying low probability events in RS images is a challenging problem given …
Automated mineralogical anomaly detection using a categorization of optical maturity trend at lunar surface
The mineralogical anomaly is the mineralogically diagnostic character that differs from its
surrounding spectra in terms of absorption features of a spectrum. On the airless planetary …
surrounding spectra in terms of absorption features of a spectrum. On the airless planetary …
Hyperspectral anomaly detection based on background purification and spectral feature extraction
M Zhao, W Zheng, J Hu - International Conference on Optical …, 2024 - spiedigitallibrary.org
Hyperspectral anomaly detection (HAD) does not require a priori information, and accurate
discrimination is made by analyzing the difference between the anomalies and the …
discrimination is made by analyzing the difference between the anomalies and the …